This application claims priority of European Patent Application No. 99308919.2, which was filed on Nov. 9, 1999.
This invention relates to a method and apparatus for filtering signals in a radio telecommunications system.
In a radio telecommunications base station, the provision of adaptive or smart antennas is known to enhance capacity, mainly because such antennas have good Co-Channel Interference (CCI) rejection capability. However perfect timeslot synchronization is assumed between a desired signal and interfering signals, and small cells must be used to allow the application of standard antenna array processing techniques.
In a system in which timeslots are not synchronized, such as GSM (Global System for Mobile Communications) and EDGE (Enhanced Data Rates for GSM Evolution), or when large cells are employed, such assumptions cannot be made.
FIG. 1 illustrates a plot of amplitude A versus time t of a desired signal D, comprising a tail band T at each end, two pay loads P, and a midamble training sequence S. FIG. 1 also shows 2 interfering signals, the first I1 being of substantially greater amplitude than the second I2, and there being a break point B between them.
The CCI of FIG. 1 can be considered as a nonstationary interference, and corresponding nonstationary processing techniques can be applied, as proposed by J Karlsson, xe2x80x9cAdaptive antennas in GSM systems with non-synchronized base stationsxe2x80x9d Licentiate""s thesis, Dept of Signals, Sensors and Systems, Royal Inst. Of Technology, Sweden, 1997, and by E Villier, L. Lopes, S Aftelak, xe2x80x9cOn application of uplink optimum combining to base station receptionxe2x80x9d in Proc. IEEE 48th VTC, pp747-752, Ottawa, 1998. A drawback of such an approach is that the techniques are not effective when a limited volume of data is available, such as the 148 symbols in a GSM timeslot.
In M C Wells, xe2x80x9cIncreasing the capacity of GSM cellular radio using adaptive antennasxe2x80x9d, IEE Proc. Communications, vol 143, no.5, pp 304-310, 1996, it is pointed out that a Spatio-Temporal Filter (STF) can be used to enhance the desired signal D and reject both parts I1 and I2 of the asynchronous CCI. However conventional adjustment algorithms such as the Least Squares (LS) estimation may not be effective when the training sequence is concentrated in one part of the burst, as in GSM. It can be seen from FIG. 1 that the training sequence S overlaps with the interfering signal I2, but there is no overlap with I1.
A solution would be to spread the training sequence S over the whole burst while keeping the total number of training symbols constant, but this would require a change of the GSM standard, which is not possible.
Another solution would be to use the symbols in the tails T as additional training symbols for CCI rejection, but this may be insufficient because there are not enough symbols.
Another solution, also proposed by Wells is to use a semi-blind algorithm with projection to the Finite Alphabet (FA); the FA property is associated with the whole timeslot of the desired signal and can be used to adjust the coefficients of a STF in asynchronous CCI conditions. This semi-blind solution uses the LS estimation based on only the training symbols as an initialization, and thus the estimator may still suffer from insufficient volume of training data overlapping part of the asynchronous CCI. Referring to FIG. 1, in GSM there will be 26 symbols available in the training sequence S, plus 3 from the right hand tail, to train an STF to reject the relatively weak interference I2, but only 3 symbols in the left hand tail T to reject the stronger interference I1.
A M Kusminskiy and D Hatzinakos, in xe2x80x9cSemi-blind estimation of spatio-temporal filter coefficients based on a training-like approachxe2x80x9d, IEEE Signal Processing Letters, vol.5 no.9 pp231-233, September 1998, propose a potential method for improving accuracy by finding a solution close to that based on an enlarged number of training symbols displaced to any position within a received slot of data, but a drawback is that complexity may be high because it increases exponentially with the number of additional training-like symbols in a slot.
A need exists for a method and apparatus for filtering signals which overcomes the disadvantages of the known methods.
In a radio telecommunications system in which each timeslot has a first tail band, a first data payload, a midamble sequence of training symbols, a second data payload, and a second tail band, in accordance with the invention a method and apparatus for filtering signals by determining which of the two ends of a timeslot suffers more from co-channel interference than the other end, selecting as training-like symbols a plurality of symbols in the data payload adjacent the tail band at said end, and utilizing the training-like symbols, the tail band symbols at said end, and the midamble training symbols in an algorithm to reject co-channel interference.
In this specification, a xe2x80x9ctraining-like symbolxe2x80x9d means an information symbol of any possible value which can be used to enlarge the available number of training data, i.e. the midamble training symbols and the tail band symbols of FIGS. 1 and 2.